The effects of regulatory uncertainty on the U.S. Acid Rain Program

Title IV of the Clean Air Act Amendments of 1990 (CAAA 1990) created the first large scale cap-and-trade program as a means to control acid rain in the United States. The program regulated the emission of sulfur dioxide (SO2) and nitrous oxide (NOx) in the atmosphere—the precursor to acid rain (formerly acid deposition). Economists have long argued for the use of market-based incentive approach as oppose to the traditional command-and-control methods for its ability to be efficient and cost-effective. Title IV went into full effect in 1995 and has been lauded among one of the most successful regulation as it was efficient in reducing SO2 at lower cost than other program. Market based or incentive based programs work by providing incentives for individuals and firms to alter polluting behavirors. This is accomplished by inposing opportunity cost through pricing. The altering of polluting bvehaviors is achieved by changes in the regulatory environment in which firms operate. However, when prices are low there is the potential for the loss of incentive. Such loss in the regulatory environment occurred in 2008 when the D.C. Circuit overturned the Clean Air Interstate Rule (CAIR) and remanded the dispute to EPA to develop new rules for its replacement. This thesis found regulatory uncertainty to contribute significantly to the decline in the price of emission permits. However, the contribution is relatively small. The adoption of technology appears to be the driving factor behind the decline in the price of emission permits. In the context of the Clean Air Act, there was the expectation of more stringent SO2 standards and impending regulation of mercury emissions. Scrubber technology used to control the emission of SO2 has also shown to be effective in limiting the emissions of oxidized mercury. Since the announcement of these standards there has been a statistically significant increase in the number of control technologies being implemented

Neural Network Based Robust Adaptive Beamforming for Smart Antenna System

As the growing demand for mobile communications is constantly increasing, the need for better coverage, improved capacity, and higher transmission quality rises. Thus, a more efficient use of the radio spectrum is required. A smart antenna system is capable of efficiently utilizing the radio spectrum and is a promise for an effective solution to the present wireless system problems while achieving reliable and robust high-speed, high-data-rate transmission. Smart antenna technology offer significantly improved solution to reduce interference level and improve system capacity. With this technology, each user’s signal is transmitted and received by the base station only in the direction of that particular user. Smart antenna technology attempts to address this problem via advanced signal processing technology called beamforming. The adaptive algorithm used in the signal processing has a profound effect on the performance of a Smart Antenna system that is known to have resolution and interference rejection capability when array steering vector is precisely known. Adaptive beamforming is used for enhancing a desired signal while suppressing noise and interference at the output of an array of sensors. However the performance degradation of adaptive beamforming may become more pronounced than in an ideal case because some of underlying assumptions on environment, sources or sensor array can be violated and this may cause mismatch. There are several efficient approaches that provide an improved robustness against mismatch as like LSMI algorithm. Neural network is a massively parallel distributed processor made up of simple processing units, which has a natural propensity for storing experimental knowledge and making it available for use. Neural network methods possess such advantages as general purpose nature, nonlinear property, passive parallelism, adaptive learning capability, generalization capability and fast convergence rates. Motivated by these inherent advantages of the neural network, in this thesis work, a robust adaptive beamforming algorithm using neural network is investigated which is effective in case of signal steering vector mismatch. This technique employs a three-layer radial basis function neural network (RBFNN), which treats the problem of computing the weights of an adaptive array antenna as a mapping problem. The robust adaptive beamforming algorithm using RBFNN, provides excellent robustness to signal steering vector mismatches, enhances the array system performance under non ideal conditions and makes the mean output array SINR (Signal-to-Interference-plus- Noise Ratio) consistently close to the optimal one

Right sided spleen laying retro-duodenal: A case report and review of the literature

Introduction: Unlike left sided accessory spleen that are seen in 10–30% of cases at autopsy, cases of right accessory spleens are extremely rare. This congenital body of healthy splenic tissue simulates tumors from neighboring organs and presents a challenge in formulating a differential diagnosis. Presentation of case: We present the case of a patient whose CT scan of the abdomen showed a large mass, 11 × 8 cm, arising retro-duodenal and lying just anterior to the right kidney. To the best of our knowledge, this is the only case where the accessory spleen was found retro-duodenal, directly anterior to the kidney and completely separate from the supra-renal gland. The chief complaint of the patient was right upper quadrant pain, radiating to the back, and colicky in nature. The patient was diagnosed with duodenal gastro-intestinal stromal tumor and a retro-peritoneal sarcoma. The mass was removed via a Kocher’s incision and immunohistological examination showed that it was a right sided accessory spleen. The patient’s left sided spleen appeared normal. Discussion: Efforts to distinguish an accessory spleen from a retroperitoneal tumor with available scans, percutaneous biopsy or biochemical tests are inconclusive. Differential diagnosis between a retroperitoneal tumor and an accessory spleen can only be made after surgical exploration. Conclusion: This case highlights the fact that surgeons should consider the possibility of an accessory spleen when making a differential diagnosis of retroperitoneal tumors